INTRODUCTION

CL5.6 - Climate Data Compilations, Homogenisation and Analysis of Variability, Trends and Extremes

POSTER # EGU2020-12298

ABSTRACTWind speed data recorded using different signal-processing procedures can introduce errors in the wind speed measurements. This study

aims to assess the effects of a set of various moving average filter durations and turbulence intensities on the recorded maximum gust wind

speeds. For this purpose, a series of wind-tunnel experiments was carried out on the widely-used Vaisala WAA151 cup anemometer. The

variations of gust factor as a function of the gust duration and turbulence intensity are presented. The wind-tunnel results are compared with

values computed from a theoretical approach, namely random process and linear system theory, and the results were also validated against

values reported in the literature where possible. The results show that the maximum gust wind speeds measured using large averaging

durations (e.g. 3 s or 5 s) lead to up to 25% – 30% negative biases compared to high frequency measurements (e.g. 4 Hz unfiltered gust

measurements). This result can strongly impact subsequent meteorological, climatological and wind engineering studies, as different gust

definitions have been adopted by National Weather Services and institutions around the world. Lastly, a set of correction factors (i.e. gust

factor ratios) have been proposed that allows measurements at a specific gust duration to be converted to equivalent measurements at

specified particular gust durations of interest.

Acknowledgements: The authors are grateful to the New Zealand MetService and NIWA for providing the anemometers for the tests. The study is partly funded by three projects: (i) New Zealand Ministry of Business, Innovation and Employment, “New Zealand Natural Hazards Platform”; (ii) Swedish Research Council, “Detection and attribution of changes in extreme wind gusts over land” (2017-03780); and (iii) Spanish Ministry of Science,

Innovation and Universities, “Evaluación y atribución de la variabilidad de la velocidad media y las rachas máximas de viento: causas del fenómeno “stilling” (RTI2018-095749-A-I00). C. Azorin-Molina is also supported by RYC-2017-22830. The authors also would like to thank Dr. Yin Fai Li, Wind Tunnel Engineer at the University of Auckland, for the fruitful discussions and helpful suggestions regarding the wind-tunnel experiments.

To summarise, the major findings of this experimental study are:

1. The results show that increasing the effective gust duration reduces both the gust

and peak factors, resulting in an underestimation of maximum gust wind speeds

and an overestimation of minimum gust wind speeds.

2. The maximum difference between gust factors obtained for high (e.g. 3-s to 5-s)

and low (raw, unfiltered measurements) gust durations reached values of 25% –

30% for the high turbulence, and up to 5% – 10% for low turbulence conditions.

3. Gust factor ratios, an important parameter that allow the measurements from a

specific gust duration to be converted to other gust durations of interest, are

reported for various gust durations as a function of turbulence intensity.

4. The differences and gust factor ratios computed in this study can be applied

directly to full-scale measurements, and can be used in several research areas.

These factors clearly play an essential role in meteorological, climatological and

wind engineering studies.

The results of the present study are being used in several ongoing research projects

by the authors.

[1] A.A. Safaei Pirooz, R.G.J. Flay, Response characteristics of anemometers used in New Zealand, in: The 19th Australasian Wind Engineering

Society Workshop, April 4-6, Torquay, Victoria, 2018

[2] R. Turner, A.A. Safaei Pirooz, R.G.J. Flay, S. Moore, M. Revell, Use of High-Resolution Numerical Models and Statistical Approaches to

Understand New Zealand Historical Wind Speed and Gust Climatologies, J. Appl. Meteorol. Climatol. 58 (2019) 1195-1218,

https://doi.org/10.1175/JAMC-D-18-0347.1.

[3] C. Azorin-Molina, J. Asin, T.R. McVicar, L. Minola, J.I. Lopez-Moreno, S.M. Vicente-Serrano, D. Chen, Evaluating anemometer drift: A statistical

approach to correct biases in wind speed measurement, Atmos. Res. 203 (2018) 175-188, https://doi.org/10.1016/j.atmosres.2017.12.010.

[4] J.D. Holmes, J.D. Ginger, The Gust Wind Speed Duration In AS/NZS 1170.2, Aust. J. Struct. Eng. 13 (2012) 207-217.

[5] C. Miller, J. Holmes, D. Henderson, J. Ginger, M. Morrison, The response of the Dines anemometer to gusts and comparisons with cup

anemometers, J. Atmos. Ocean. Technol. 30 (2013) 1320-1336, https://doi.org/10.1175/JTECH-D-12-00109.1.

Figure 1. Annual maximum gust wind speeds recorded at: (a) Auckland; (b) Wellington

Amir A. Safaei Pirooz1, Richard G.J. Flay1, Lorenzo Minola2, Cesar Azorin-Molina2,3 , Deliang Chen2

1 Department of Mechanical Engineering, The University of Auckland, Auckland 1142, New Zealand

2 Regional Climate Group, Department of Earth Sciences, University of Gothenburg, Gothenburg, Sweden

3 Centro de Investigaciones sobre Desertificación – Spanish National Research Council (CIDE-CSIC), Moncada (Valencia), Spain

Contact: Amir A. S. Pirooz, asaf433@aucklanduni.ac.nz

CONCLUSIONS

METHODOLOGY

RESULTS

DISCUSSION

SELECTED REFERENCES

Effects of Sensor Response and Gust Duration on Maximum Wind Gust Measurements

and Data Homogenisation

Figure 4. Turbulence

intensities of wind

produced in the wind

tunnel measured by the

reference Cobra sensor

Figure 3. Example of wind tunnel setup for generating turbulence

Figure 5. Effect of applying moving average to the wind speed recorded by a WAA151 anemometer in a turbulent wind

with 𝐼𝑢=32.4% and ഥ𝑈 =10.1 m s‒1: (a) Power spectral densities; (b) Wind speed time series.

Wind-tunnel (WT) experiments were carried out to consider the real

response characteristics of the anemometer and recording system.

For comparison and validation purposes, the WT results have been

compared with theoretical results, using the properties of the full-scale

(FS) wind flow, and also with values reported in the literature [4,5].

Figure 6. Comparison between the gust factor ratios obtained

from WT tests and the theoretical approach (i.e. FS conditions),

and those reported by Holmes and Ginger [4] and Miller et al. [5]. Figure 7. Gust factor ratios and errors between: (a) 3-s and raw measurements (4 Hz); (b) 3-s and 2-s gusts

Wind Tunnel Experiments

Theoretical Approach: Random process

and linear system theory

Parameters for ComparisonTwo parameters were defined to quantify the difference between

parameters 𝜑 (e.g. GF) at various gust durations (i.e. d1 and d2).

𝜺 =𝝋𝒅𝟏 −𝝋𝒅𝟐

𝝋𝒅𝟏× 𝟏𝟎𝟎 (𝐄𝐪. 𝟏) 𝑹 =

𝑮𝑭𝒅𝟏𝑮𝑭𝒅𝟐

(𝐄𝐪. 𝟐)

(a) (b)

Excellent agreement was achieved between the differences and gust

factor ratios computed from the WT tests, the theoretical approach, and

values reported in the literature.

Change in the gust duration can result in breakpoints in wind speed

time series. Also, gust duration can significantly affect the subsequent

analyses, such as trend and extreme value analyses. Results

demonstrated that the difference between high and low gust-duration

gust measurements can be as large as 30 – 35%. Therefore, the gust

duration must be taken into account when homogenising historical wind

data.

WT experiment, theoretical approach and FS measurements are

complementary methods contributing to better understanding of the

differences between wind measuring instruments and recording

procedures, including gust duration. Unlike the theoretical approach, in

WT experiments, the true response characteristics of both the

anemometer and the data logger are accounted for. However, on the

other hand, compared with the atmospheric boundary layer (ABL), the

replicated turbulence in the WT is at higher frequencies and contains

much smaller turbulence integral length scales. However, for the

theoretical FS approach, the turbulence length scales corresponding to

the FS ABL can be used.

An alternative approach is to conduct FS experiments, as they do not

require any assumptions and simplifications in both the anemometer

response characteristics and the ABL turbulence. However, in this

approach the experiments are less controllable compared to the wind

tunnel.

Issue: Historical wind data have been recorded using different

instruments and gust durations (e.g. Fig. 2). Particularly after the

implementation of Automatic Weather Stations (AWS) and 3-s gust

definition in the 1990s.

These changes have resulted in breakpoints and discontinuities in

wind time series (e.g. Fig. 1).

Figure 2.

Anemometers used

in New Zealand

Objectives of Study: Quantitatively assess the effects of gust duration on

gust wind speed measurements.

Propose correction factors (i.e. Gust Factor (GF) ratios

Eq. 2) that can be used for the homogenisation of wind

speed time series and for converting measurements

with a certain gust duration to equivalent gust

measurements with different gust durations.

Vaisala WAA151 cup anemometer was used for the present tests.

Tests were carried out in the boundary-layer WT at the University

of Auckland, New Zealand, which has a max speed of 20 m/s, and

cross-section of 3.6 m× 2.5 m (width× height).

Turbulence-inducing elements (Fig. 3) were used in the WT to

replicate the random fluctuations of wind in nature. Turbulence

intensities of the flow in WT are shown in Fig. 4.

Due to the smaller turbulence integral length scales (λ) inside the WT compared to FS, a

theoretical approach, i.e. random process and linear system theory [4, 5], was employed, where

the corresponding FS λ were used, to compute GF and to compare them with the WT results.

Applying a moving average filter reduces the area

under the wind spectrum (Fig. 5a), and smoothens

the wind fluctuations Fig. 5b, which consequently

affect the gust factor.

Fig. 6 shows GF ratios (Eq. 2) obtained from WT

tests, theoretical method, and literature [4,5]. Results

agreed well with less than 1.5% and 3.5% differences

for low and high turbulence cases, respectively.

GF ratios (Eq. 2) and errors (Eq. 1) for two sets of

gust durations are shown in Fig. 7 as a function of

turbulence intensity. In high turbulence conditions,

GF ratios in the order of 1.25-1.30 (Fig. 7a) and 1.03-

1.05 (Fig. 7b) are required to convert 3-s gusts to raw

4Hz and 2-s gusts, respectively.

Complete sets of correction factors for various gust

durations will be reported in a full paper.